The present invention relates to a music information retrieval system capable of retrieving songs that have similar voice timbres.
In recent years, music retrieval has added importance. Because of rapid and widespread diffusion of portable audio players and online music sales services, users can retrieve a favorite song from among a vast amount of songs and can listen to any music they desire to do so, at anytime and anywhere. This trend has triggered a demand to discover a song that a user has never heard before, using his favorite song as a key for the discovery. When the query of the song targeted for retrieval is not known and only vague information such as “preference” is available, the conventional method of searching for songs that only use bibliographic information such as the name of an artist or the name of a music genre is useless. In view of such a trend, a lot of studies on a music retrieval system based on the content of a song have been conducted, as shown in the following Nonpatent Documents 1 through 9.    [Nonpatent Document 1] Aucouturier, J.-J. and Pachet, F.: Music Similarity Measures: What's the Use?, Proceedings of the 3rd International Conference on Music Information Retrieval (IS-MIR2002), pp. 157-163 (2002).    [Nonpatent Document 2] Logan, B.: Content-Based Playlist Generation: Ex-ploratory Experiments, Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR2002), pp. 295-296 (2003).    [Nonpatent Document 3] Allamanche, E., Herre, J., Hellmuth, O., Kastner, T. and Ertel, C.: A Multiple Feature Model for Musical Similarity Retrieval, Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR2003), pp. 217-218 (2003).    [Nonpatent Document 4] Berenzweig, A., Logan, B., Ellis, D. P. W. and Whit-man, B.: A Large-Scale Evaluation of Acoustic and Subjective Music Similarity Measures, Computer Music Journal, Vol. 28, No. 2, pp. 63-76 (2004).    [Nonpatent Document 5] McKinney, M. F. and Breebaart, J.: Features for audio and music classification, Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR2003), pp. 151-158 (2003).    [Nonpatent Document 6] Tzanetakis, G., Gao, J. and Steenkiste, P.: A Scalable Peer-to-Peer System for Music Content and Information Retrieval, Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR2003), pp. 209-214 (2003).    [Nonpatent Document 7] Pampalk, E., Flexer, A. and Widmer, G.: Improvements of Audio-based Music Similarity and Genre Classification, Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR2005), pp. 628-633 (2005)    [Nonpatent Document 8] Flexer, A., Gouyou, F., Dixon, S. and Widmer, G.: Probabilistic combination of features for music classification, Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR2006), pp. 628-633 (2006).    [Nonpatent Document 9] Pohle, T., Knees, P., Schedl, M. and Widmer, G.: Independent Component Analysis for Music Similarity Computation, Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR2006), pp. 228-233 (2006)
Music retrieval techniques disclosed in these studies, however, use acoustic features such as Mel-Frequency Cepstrum Coefficient (MFCC), spectral centroid, rolloff, and flux that represent musical timbres of songs, for expressing musical content, and do not use features such as voice timbre, for expressing more detailed musical content. For this reason, conventionally, songs with similar voice timbres cannot be retrieved.